Spatial-Scale Effects on Relative Importance of Physical Habitat Predictors of Stream Health

A common theme in recent landscape studies is the comparison of riparian and watershed land use as predictors of stream health. The objective of this study was to compare the performance of reach-scale habitat and remotely assessed watershed-scale habitat as predictors of stream health over varying spatial extents. Stream health was measured with scores on a fish index of biotic integrity (IBI) using data from 95 stream reaches in the Eastern Corn Belt Plain (ECBP) ecoregion of Indiana. Watersheds hierarchically nested within the ecoregion were used to regroup sampling locations to represent varying spatial extents. Reach habitat was represented by metrics of a qualitative habitat evaluation index, whereas watershed variables were represented by riparian forest, geomorphology, and hydrologic indices. The importance of reach- versus watershed-scale variables was measured by multiple regression model adjusted-R² and best subset comparisons in the general linear statistical framework. Watershed models had adjusted-R² ranging from 0.25 to 0.93 and reach models had adjusted-R² ranging from 0.09 to 0.86. Better-fitting models were associated with smaller spatial extents. Watershed models explained about 15% more variation in IBI scores than reach models on average. Variety of surficial geology contributed to decline in model predictive power. Results should be interpreted bearing in mind that reach habitat was qualitatively measured and only fish assemblages were used to measure stream health. Riparian forest and length-slope (LS) factor were the most important watershed-scale variables and mostly positively correlated with IBI scores, whereas substrate and riffle-pool quality were the important reach-scale variables in the ECBP.     

EVALUATION OF INFLOW TO MIRROR LAKE,NEW HAMPSHIRE1

ABSTRACT: Measured stream discharge plus calculated ground water discharge (total measured runoff) were compared with runoff calculated by the unit-runoff method for the two largest watersheds of Mirror Lake for 1981–1983. Runoff calculated by the unit-runoff method, using Hubbard Brook watershed 3 as the index watershed, was greater than the total measured runoff into Mirror Lake during periods of high flow and slightly less than the total measured runoff into Mirror Lake during periods of low flow. Annual calculated unit runoff was 17 to 37 percent greater than total measured runoff. Differences in monthly runoff are far greater, ranging from 0 to greater than 100 percent. For high flows the calculated unit runoff is about 2 times greater than total measured runoff. For low flows the northwest basin of Mirror Lake has the greatest ground water contribution compared to the other two basins. In contrast, Hubbard Brook watershed 3 has the least ground water contribution.     

A METHOD FOR ESTIMATING SNOWFALL AMOUNTS1

ABSTRACT: Long-term climatic data from National Weather Service stations in six areas of the United States were utilized to develop regression equations relating a “snowfall index” parameter and air temperature. Nearly 200 stations, representing a wide range in physiographic and climatic conditions, were selected for analysis. Snowfall index is defined as the ratio of snowfall depth to precipitation. Using annual data, regression analysis indicated snowfall index to be significantly (α= 0.01) related to temperature for five of the six areas studied. Differences between equations were attributed to the effects of precipitation and temperature during non-snowfall periods. Mean monthly data were also considered and significant equations (α= 0.011, representing a family of similarly shaped curves, were obtained. The illustrated equations can be used for estimating mean monthly and annual snowfall amounts for stations having only temperature and precipitation measurements.     

Bison and cattle grazing management,bare ground coverage,and links to suspended sediment concentrations in grassland streams

This study quantified the impact of bison and cattle grazing management practices on bare ground coverage at the watershed, riparian, and forested riparian scales within the Flint Hills ecoregion in Kansas. We tested for correlations between bare ground coverage and fluvial suspended sediment concentrations during base‐flow and storm‐flow events. We used remotely sensed imagery combined with field surveys to classify ground cover and quantify the presence of bare ground. Base‐flow water samples were collected bi‐monthly during rain‐free periods and 24 h following precipitation events. Storm‐flow water samples were collected on the rising limb of the hydrograph, using single‐stage automatic samplers. Ungrazed treatments contained the lowest coverage of bare ground at the watershed, riparian, and forested riparian scales. Bison treatments contained the highest coverage of bare ground at the watershed scale, while high‐density cattle treatments contained the highest coverage of bare ground at the riparian and forested riparian scales. In bison and cattle‐grazed treatments, a majority of bare ground was located near fence lines, watershed boundaries, and third‐ and fourth‐order stream segments. Inorganic sediment concentrations at base flow were best predicted by riparian bare ground coverage, while storm‐flow sediment concentrations were best predicted by watershed scale bare ground coverage.     

FORESTS AND OTHER FACTORS ASSOCIATED WITH STREAMFLOWS IN EAST TEXAS1

Effects of proportion of watersheds in forest and watershed physiographic factors on mean annual streamflow (1965-76), median flow, and 12 flood flow characteristics were regionally analyzed for 19 unregulated streams in East Texas. Annual streamflow increased with decreasing proportion of forest area. Differences in annual streamflow between full forest cover and bare watersheds could be as much as 200 mm. Other things being equal, the minimum watershed area required to generate 0.142 cm (5 cfs), a criterion used by the U.S. Corps of Engineering in regulating dredge and fill activity for water pollution abatement in East Texas streams, is 70 km² (27 mi²). Of the 31 physio-climatic parameters analyzed, watershed area, percent forest area, shape index, spring precipitation, and annual temperature were the most significant in affecting streamflow characteristics in East Texas. Using 2-3 of these five variables, all of the 14 streamflow characteristics can be estimated with accuracy ranging from acceptable to excellent levels.     

FOG DRIP IN THE BULL RUN MUNICIPAL WATERSHED,OREGON1

ABSTRACT: Net precipitation under old growth Douglas fir forest in the Bull Run Municipal Watershed (Portland, Oregon) totaled 1739 mm during a 4Cbweek period, 387 mm more than in adjacent clearcut areas. Expressing data on a full water year basis and adjusting gross precipitation for losses due to rainfall interception suggest fog drip could have added 882 mm (35 in) of water to total precipitation during a year when precipitation measured 2160 mm in a rain gage in a nearby clearing. Standard rain gages installed in open areas where fog is common may be collecting up to 30 percent less precipitation than would be collected in the forest. Long term forest management (Le., timber harvest) in the watershed could reduce annual water yield and, more importantly, summer stream flow by reducing fog drip.     

STREAM ASSESSMENTS USING BIOTIC INDICES: RESPONSES TO PHYSICOCHEMICAL VARIABLES1

ABSTRACT: Responses of the Wyoming Stream Integrity Index (WSII), a regionally calibrated multimetric index, were investigated in relation to background elevational changes in water quality and habitat conditions versus accelerated anthropogenic degradation at the watershed scale. Assessments were conducted for three rivers in southeast Wyoming: the Little Medicine Bow River, the Medicine Bow River, and Rock Creek. Pearson correlation coefficients and regression models related “core metrics” and index scores to elevational gradients of physicochemical variables. Velocity, substrate, and weighted habitat values were positively correlated to index scores, while suspended solids was negatively correlated. The exclusive dependence of index scores on physical variables specifies the type of environmental gradients the WSII is most robust in detecting. The individual “core metrics” Plecoptera taxa, Trichoptera taxa, percent Trichoptera without Hydropsychidae, and percent noninsects appeared most sensitive to physical changes and were thus driving associations between index scores and physical variables. Despite strong correlations with physical variables, anomalies existed where habitat conditions were good, unknown stressors existed, or gradients were naturally occurring despite “Poor” index scores (i.e., degraded stream conditions). Such findings illustrate the influence of regional variability on biotic indices and the importance of identifying sufficient reference and impaired stream reaches used to develop and calibrate multimetric indices relying on reference conditions.     

CONNECTING GROUND WATER INFLUXES WITH FISH SPECIES DIVERSITY IN AN URBANIZED WATERSHED1

ABSTRACT: Valley Creek watershed is a small stream system that feeds the Schuylkill River near Philadelphia, Pennsylvania. The watershed is highly urbanized, including over 17 percent impervious surface cover (ISC) by area. Imperviousness in a watershed has been linked to fish community structure and integrity. Generally, above 10 to 12 percent ISC there is marked decline in fish assemblages with fish being absent above 25 percent ISC. This study quantifies the importance of ground water in maintaining fish species diversity in subbasins with over 30 percent ISC. Valley Creek contains an atypical fish assemblage in that the majority of the fish are warm‐water species, and the stream supports naturally reproducing brown trout, which were introduced and stocked from the early 1900s to 1985. Fish communities were quantified at 13 stations throughout the watershed, and Simpson's species diversity index was calculated. One hundred and nine springs were located, and their flow rates measured. A cross covariance analysis between Simpson's species diversity index and spring flow rates upstream of fish stations was performed to quantify the spatial correlation between these two variables. The correlation was found to be highest at lag distances up to about 400 m and drop off significantly beyond lag distances of about 800 m.     

THROUGHFALL pH: EFFECT OF PRECIPITATION : TIMING AND AMOUNT1

ABSTRACT: Precipitation, throughfall, and stream pH were measured weekly over a 27-week period in 1982 on the Little Millseat watershed in eastern Kentucky. The average pH values over the study period were 4.3, 4.9, and 6.4, respectively, indicating significant buffering as water moved from the atmosphere, through the deciduous canopy, and through or over the soil to the stream. Regression analysis demonstrated that the timing and amount of precipitation were important factors influencing the pH of the throughfall. Weekly precipitation and the three-week average precipitation were statistically significant variables, explaining 53 percent of the variance in the observed through- fall pH. Precipitation pH was not a statistically significant variable for this watershed and sampling period.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART II: MODEL APPLICATION1

ABSTRACT: This paper describes the application of a river basin scale hydrologic model (described in Part I) to Richland and Chambers Creeks watershed (RC watershed) in upper Trinity River basin in Texas. The inputs to the model were accumulated from hydro-graphic and geographic databases and maps using a raster-based GIS. Available weather data from 12 weather stations in and around the watershed and stream flow data from two USGS stream gauge station for the period 1965 to 1984 were used in the flow calibration and validation. Sediment calibration was carried out for the period 1988 through 1994 using the 1994 sediment survey data from the Richland-Chambers lake. Sediment validation was conducted on a subwatershed (Mill Creek watershed) situated on Chambers Creek of the RC watershed. The model was evaluated by well established statistical and visual methods and was found to explain at least 84 percent and 65 percent of the variability in the observed stream flow data for the calibration and validation periods, respectively. In addition, the model predicted the accumulated sediment load within 2 percent and 9 percent from the observed data for the RC watershed and Mill Creek watershed, respectively.     

STATISTICAL LOW FLOW ESTIMATION USING GIS ANALYSIS IN HUMID MONTANE REGIONS IN PUERTO RICO1

ABSTRACT: Statistical analysis of watershed parameters derived using a Geographical Information system (GIS) was done to develop equations for estimating the 7d–10yr, 30d–10yr, and 7d–2yr low flow for watersheds in humid montane regions of Puerto Rico. Digital elevation models and land use, geology, soils, and stream network coverages were used to evaluate 21 geomorphic, 10 stream channel, 9 relief, 7 geology, 4 climate, and 2 soil parameters for each watershed. To assess which parameters should be used for further investigation, a correlation analysis was used to determine the independence and collinearity among these parameters and their relationship with low flows. Multiple regression analyses using the selected parameters were then performed to develop the statistical models of low flows. The final models were selected in the basis of the Mallow Cp statistic, the adjusted R², the Press statistic, the degree of collinearity, and an analysis of the residuals. In the final models, drainage density, the ratio of length of tributaries to the length of the main channel, the percent of drainage area with northeast aspect, and the average weighted slope of the drainage were the most significant parameters. The final models had adjusted standard errors of 58.7 percent, 59.2 percent, and 48.6 percent for the 7d–10yr, 30d–10yr, and 7d–2yr low flows respectively. For comparison, the best model based on watershed parameters that can be easily measured without a GIS had an adjusted standard error of 82.8 percent.     

REGIONAL HYDROLOGIC RESPONSE OF LOBLOLLY PINE TO AIR TEMPERATURE AND PRECIPITATION CHANGES1

ABSTRACT: Large deviations in average annual air temperatures and total annual precipitation were observed across the southern United States during the last 50 years, and these fluctuations could become even larger during the next century. We used PnET-IIS, a monthly time-step forest process model that uses soil, vegetation, and climate inputs to assess the influence of changing climate on southern U.S. pine forest water use. After model predictions of historic drainage were validated, the potential influences of climate change on loblolly pine forest water use was assessed across the region using historic (1951 to 1984) monthly precipitation and air temperature which were modified by two general circulation models (GCMs). The GCMs predicted a 3.2°C to 7.2°C increase in average monthly air temperature, a -24 percent to + 31 percent change in monthly precipitation and a -1 percent to + 3 percent change in annual precipitation. As a comparison to the GCMs, a minimum climate change scenario using a constant 2°C increase in monthly air temperature and a 20 percent increase in monthly precipitation was run in conjunction with historic climate data. Predicted changes in forest water drainage were highly dependent on the GCM used. PnET-IIS predicted that along the northern range of loblolly pine, water yield would decrease with increasing leaf area, total evapotranspiration and soil water stress. However, across most of the southern U.S., PnET-IIS predicted decreased leaf area, total evapotranspiration, and soil water stress with an associated increase in water yield. Depending on the GCM and geographic location, predicted leaf area decreased to a point which would no longer sustain loblolly pine forests, and thus indicated a decrease in the southern most range of the species within the region. These results should be evaluated in relation to other changing environmental factors (i.e., CO₂ and O₃) which are not present in the current model.     

ESTIMATION OF STREAMFLOW,BASE FLOW,AND NITRATE‐NITROGEN LOADS IN IOWA USING MULTIPLE LINEAR REGRESSION MODELS1

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest.     

Long‐Term Streamflow Response to Climatic Variability in the Loess Plateau,China1

Abstract: The Loess Plateau region in northwestern China has experienced severe water resource shortages due to the combined impacts of climate and land use changes and water resource exploitation during the past decades. This study was designed to examine the impacts of climatic variability on streamflow characteristics of a 12‐km² watershed near Tianshui City, Gansu Province in northwestern China. Statistic analytical methods including Kendall’s trend test and stepwise regression were used to detect trends in relationship between observed streamflow and climatic variables. Sensitivity analysis based on an evapotranspiration model was used to detect quantitative hydrologic sensitivity to climatic variability. We found that precipitation (P), potential evapotranspiration (PET) and streamflow (Q) were not statistically significantly different (p > 0.05) over the study period between 1982 and 2003. Stepwise regression and sensitivity analysis all indicated that P was more influential than PET in affecting annual streamflow, but the similar relationship existed at the monthly scale. The sensitivity of streamflow response to variations of P and PET increased slightly with the increase in watershed dryness (PET/P) as well as the increase in runoff ratio (Q/P). This study concluded that future changes in climate, precipitation in particular, will significantly impact water resources in the Loess Plateau region an area that is already experiencing a decreasing trend in water yield.     

WEST AFRICA: VOLTA DISCHARGE DATA QUALITY ASSESSMENT AND USE1

ABSTRACT: Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets.     

STREAM FLOW IN RELATION TO OHIA FOREST DECLINE ON THE ISLAND OF HAWAII1

ABSTRACT: Dieback of the ohia forest over a large part of the Hilo watershed and adjacent areas has resulted in a severe loss of the overstory crown component of the vegetation. The decline could cause serious damage to the watershed. To evaluate possible changes in conditions in the Hilo area since the decline began, stream flow, water quality, and precipitation data from 1929 to 1980 were collected and analyzed. The limited data available do not indicate that the ohia decline has resulted in a significant change in either annual stream flow or peak stream flow of a stream discharging from the ohia forest in the Hilo area. Suspended sediment production of two streams remains well within accepted levels as does the chemical makeup of components dissolved in the streams.     

IMPACTS OF CALIFORNIA'S CLIMATIC REGIMES AND COASTAL LAND USE CHANGE ON STREAMFLOW CHARACTERISTICS1

ABSTRACT: To investigate the impacts of urbanization and climatic fluctuations on stream flow magnitude and variability in a Mediterranean climate, the HEC‐HMS rainfall/runoff model is used to simulate stream flow for a 14‐year period (October 1, 1988, to September 30, 2002) in the Atascadero Creek watershed located along the southern coast of California for 1929, 1998, and 2050 (estimated) land use conditions (8, 38 and 52 percent urban, respectively). The 14‐year period experienced a range of climatic conditions caused mainly by El Nino‐Southern Oscillation variations. A geographic information system is used to delineate the watershed and parameterize the model, which is calibrated using data from two stream flow and eight rainfall gauges. Urbanization is shown to increase peak discharges and runoff volume while decreasing stream flow variability. In all cases, the annual and 14‐year distributions of stream flow are shown to be highly skewed, with the annual maximum 24 hours of discharge accounting for 22 to 52 percent of the annual runoff and the maximum ten days of discharge from an average El Nino year producing 10 to 15 percent of the total 14‐year discharge. For the entire period of urbanization (1929 to 2050), the average increase in annual maximum discharges and runoff was 45 m³/s (300 percent) and 15 cm (350 percent), respectively. Additionally, the projected increase in urbanization from 1998 to 2050 is half the increase from 1929 to 1998; however, increases in runoff (22 m³/s and 7 cm) are similar for both scenarios because of the region's spatial development pattern.     

IMPACTS OF CLIMATE CHANGE ON WATER YIELD IN THE UPPER WIND RIVER BASIN1

ABSTRACT: The potential impacts of climate change on water yield are examined in the Upper Wind River Basin. This is a high‐elevation, mountain basin with a snowfall/snowmelt dominated stream‐flow hydrograph. A variety of physiographic conditions are represented in the rangeland, coniferous forests, and high‐elevation alpine regions. The Soil Water Assessment Tool (SWAT) is used to model the baseline input time series data and climate change scenarios. Five hydroclimatic variables (temperature, precipitation, CO₂, radiation, and humidity) are examined using sensitivity tests of individual and coupled variables with a constant change and coupled variables with a monthly change. Results indicate that the most influential variable on annual water yield is precipitation; and, the most influential variable on the timing of streamflow is temperature. Carbon dioxide, radiation, and humidity each noticeably impact water yield, but less significantly. The coupled variable analyses represent a more realistic climate change regime and reflect the combined response of the basin to each variable; for example, increased temperature offsets the effects of increased precipitation and magnifies the effects of decreased precipitation. This paper shows that the hydrologic response to climate change depends largely on the hydroclimatic variables examined and that each variable has a unique effect (e.g., magnitude, timing) on water yield.     

GENERALIZED WATERSHED LOADING FUNCTIONS FOR STREAM FLOW NUTRIENTS1

ABSTRACT: Loading functions are proposed as a general model for estimating monthly nitrogen and phosphorus fluxes in stream flow. The functions have a simple mathematical structure, describe a wide range of rural and urban nonpoint sources, and couple surface runoff and ground water discharge. Rural runoff loads are computed from daily runoff and erosion and monthly sediment yield calculations. Urban runoff loads are based on daily nutrient accumulation rates and exponential wash off functions. Ground water discharge is determined by lumped parameter unsaturated and saturated zone soil moisture balances. Default values for model chemical parameters were estimated from literature values. Validation studies over a three-year period for an 850 km² watershed showed that the loading functions explained at least 90 percent of the observed monthly variation in dissolved and total nitrogen and phosphorus fluxes in stream flow. Errors in model predictions of mean monthly fluxes were: dissolved phosphorus - 4 percent; total phosphorus - 2 percent; dissolved nitrogen - 18 percent; and total nitrogen - 28 percent. These results were obtained without model calibration.